Multilevel Statistical Modeling for Proteomic Experiments With Complex Designs and Isobaric Labeling
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Dive into a 46-minute webinar on multilevel statistical modeling for proteomic experiments with complex designs and isobaric labeling, presented by Dr. Olga Vitek. Explore how quantitative mass spectrometry-based proteomic experiments are designed to answer increasingly complex questions, such as characterizing changes in protein abundance in biological samples collected repeatedly over time and across multiple conditions. Learn from Dr. Vitek's extensive experience, including her PhD in Statistics from Purdue University and postdoctoral work at the Institute for Systems Biology in Seattle. Gain insights into advanced statistical techniques for analyzing complex proteomic data and their applications in cutting-edge research.
Syllabus
Multilevel Statistical Modeling for Proteomic Experiments With Complex Designs and Isobaric Labeling
Taught by
Labroots